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A classification of disease mapping methods.

J F Bithell1

  • 1Department of Statistics, University of Oxford, 1 South Parks Road, Oxford OX1 3TG, UK. bithell@stats.ox.ac.uk

Statistics in Medicine
|August 29, 2000
PubMed
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This study classifies methods for mapping disease incidence, evaluating techniques for time, projection, and data types. The relative risk function is proposed as a benchmark for assessing flawed or untested mapping approaches.

Area of Science:

  • Epidemiology
  • Geographic Information Systems (GIS)
  • Statistical Modeling

Background:

  • Depicting disease incidence on maps is crucial for public health.
  • Existing methods for disease mapping vary widely in their approach and statistical rigor.
  • There is a need for a systematic classification and evaluation of these mapping techniques.

Purpose of the Study:

  • To classify methods for depicting disease incidence on geographical maps.
  • To evaluate the suitability of different mapping techniques, considering factors like time and population density.
  • To introduce a fundamental model for assessing the statistical properties of these methods.

Main Methods:

  • Comparative classification of disease mapping methods.
  • Discussion of temporal and projection-based mapping approaches.

Related Experiment Videos

  • Distinction between non-parametric and model-based (including Bayesian) methods for areal data.
  • Consideration of point-referenced data.

    • Main Results:

    • Identified underlying principles for effective disease incidence mapping.
    • Evaluated methods for independence from population density.
    • Highlighted the utility of the relative risk function as a benchmark.
    • Noted that many existing methods are flawed or statistically untested.

    Conclusions:

    • A structured approach to classifying disease mapping methods is presented.
    • The relative risk function offers a valuable framework for evaluating mapping techniques.
    • Further validation of statistical properties for mapping methods is recommended.